Updated to support news and fundamentals analysis for non-openai llms

cli/main.py

@@ -771,7 +771,7 @@ def run_analysis():
             func(*args, **kwargs)
             timestamp, message_type, content = obj.messages[-1]
             content = content.replace("\n", " ")  # Replace newlines with spaces
-            with open(log_file, "a") as f:
+            with open(log_file, "a", encoding="utf-8") as f:
                 f.write(f"{timestamp} [{message_type}] {content}\n")
         return wrapper
     
@@ -782,7 +782,7 @@ def run_analysis():
             func(*args, **kwargs)
             timestamp, tool_name, args = obj.tool_calls[-1]
             args_str = ", ".join(f"{k}={v}" for k, v in args.items())
-            with open(log_file, "a") as f:
+            with open(log_file, "a", encoding="utf-8") as f:
                 f.write(f"{timestamp} [Tool Call] {tool_name}({args_str})\n")
         return wrapper
 
@@ -795,7 +795,7 @@ def run_analysis():
                 content = obj.report_sections[section_name]
                 if content:
                     file_name = f"{section_name}.md"
-                    with open(report_dir / file_name, "w") as f:
+                    with open(report_dir / file_name, "w", encoding="utf-8") as f:
                         f.write(content)
         return wrapper
 

tradingagents/dataflows/interface.py

@@ -14,6 +14,8 @@ from tqdm import tqdm
 import yfinance as yf
 from openai import OpenAI
 from .config import get_config, set_config, DATA_DIR
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_anthropic import ChatAnthropic
 
 
 def get_finnhub_news(
@@ -704,8 +706,9 @@ def get_YFin_data(
 
 def get_stock_news_openai(ticker, curr_date):
     config = get_config()
+    provider = config["llm_provider"].lower()
+    if provider == "openai":
         client = OpenAI(base_url=config["backend_url"])
-
         response = client.responses.create(
             model=config["quick_think_llm"],
             input=[
@@ -733,14 +736,46 @@ def get_stock_news_openai(ticker, curr_date):
             top_p=1,
             store=True,
         )
-
         return response.output[1].content[0].text
+    else:
+        # Use Finnhub and Google News/Reddit for real news/social data
+        news = get_finnhub_news(ticker, curr_date, 7)
+        reddit = get_reddit_company_news(ticker, curr_date, 7, 5)
+        google_news = get_google_news(ticker, curr_date, 7)
+        context = f"""
+# Finnhub News
+{news}
 
+# Reddit News
+{reddit}
+
+# Google News
+{google_news}
+"""
+        prompt = (
+            f"Given the following real company news and social data for {ticker} as of {curr_date}, "
+            "write a detailed news and sentiment analysis. Summarize key events, sentiment, and any trends that would affect trading. "
+            "Present the information in a markdown table at the end.\n\n"
+            f"{context}"
+        )
+        if provider == "google":
+            google_api_key = os.getenv("GOOGLE_API_KEY")
+            llm = ChatGoogleGenerativeAI(model=config["quick_think_llm"], google_api_key=google_api_key)
+            result = llm.invoke(prompt)
+            return result.content
+        elif provider == "anthropic":
+            anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
+            llm = ChatAnthropic(model_name=config["quick_think_llm"], api_key=anthropic_api_key)
+            result = llm.invoke(prompt)
+            return result.content
+        else:
+            return "Stock news retrieval is not supported for this LLM provider."
 
 def get_global_news_openai(curr_date):
     config = get_config()
+    provider = config["llm_provider"].lower()
+    if provider == "openai":
         client = OpenAI(base_url=config["backend_url"])
-
         response = client.responses.create(
             model=config["quick_think_llm"],
             input=[
@@ -768,14 +803,41 @@ def get_global_news_openai(curr_date):
             top_p=1,
             store=True,
         )
-
         return response.output[1].content[0].text
+    else:
+        reddit = get_reddit_global_news(curr_date, 7, 5)
+        google_news = get_google_news("global macroeconomics", curr_date, 7)
+        context = f"""
+# Reddit Global News
+{reddit}
 
+# Google News
+{google_news}
+"""
+        prompt = (
+            f"Given the following real global and macroeconomic news as of {curr_date}, "
+            "write a detailed macroeconomic news analysis. Summarize key events, sentiment, and any trends that would affect trading. "
+            "Present the information in a markdown table at the end.\n\n"
+            f"{context}"
+        )
+        if provider == "google":
+            google_api_key = os.getenv("GOOGLE_API_KEY")
+            llm = ChatGoogleGenerativeAI(model=config["quick_think_llm"], google_api_key=google_api_key)
+            result = llm.invoke(prompt)
+            return result.content
+        elif provider == "anthropic":
+            anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
+            llm = ChatAnthropic(model_name=config["quick_think_llm"], api_key=anthropic_api_key)
+            result = llm.invoke(prompt)
+            return result.content
+        else:
+            return "Global news retrieval is not supported for this LLM provider."
 
 def get_fundamentals_openai(ticker, curr_date):
     config = get_config()
+    provider = config["llm_provider"].lower()
+    if provider == "openai":
         client = OpenAI(base_url=config["backend_url"])
-
         response = client.responses.create(
             model=config["quick_think_llm"],
             input=[
@@ -803,5 +865,48 @@ def get_fundamentals_openai(ticker, curr_date):
             top_p=1,
             store=True,
         )
-
         return response.output[1].content[0].text
+    else:
+        # Fetch fundamentals from Yahoo Finance
+        import yfinance as yf
+        ticker_obj = yf.Ticker(ticker)
+        info = ticker_obj.info
+        financials = ticker_obj.financials
+        balance_sheet = ticker_obj.balance_sheet
+        cashflow = ticker_obj.cashflow
+        # Compose a context string
+        context = f"""
+# Company Info
+Name: {info.get('shortName', 'N/A')}
+Industry: {info.get('industry', 'N/A')}
+Sector: {info.get('sector', 'N/A')}
+Country: {info.get('country', 'N/A')}
+Website: {info.get('website', 'N/A')}
+
+# Financials (last available)
+{financials.to_string() if not financials.empty else 'N/A'}
+
+# Balance Sheet (last available)
+{balance_sheet.to_string() if not balance_sheet.empty else 'N/A'}
+
+# Cash Flow (last available)
+{cashflow.to_string() if not cashflow.empty else 'N/A'}
+"""
+        prompt = (
+            f"Given the following real company data for {ticker} as of {curr_date}, "
+            "write a detailed fundamental analysis. Include company profile, financials, PE/PS/Cash flow, and any recent news or events that would affect fundamentals. "
+            "Present the information in a markdown table at the end.\n\n"
+            f"{context}"
+        )
+        if provider == "google":
+            google_api_key = os.getenv("GOOGLE_API_KEY")
+            llm = ChatGoogleGenerativeAI(model=config["quick_think_llm"], google_api_key=google_api_key)
+            result = llm.invoke(prompt)
+            return result.content
+        elif provider == "anthropic":
+            anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
+            llm = ChatAnthropic(model_name=config["quick_think_llm"], api_key=anthropic_api_key)
+            result = llm.invoke(prompt)
+            return result.content
+        else:
+            return "Fundamental data retrieval is not supported for this LLM provider."

tradingagents/graph/trading_graph.py

@@ -65,8 +65,9 @@ class TradingAgentsGraph:
             self.deep_thinking_llm = ChatAnthropic(model_name=self.config["deep_think_llm"], base_url=self.config["backend_url"], timeout=120, stop=None)
             self.quick_thinking_llm = ChatAnthropic(model_name=self.config["quick_think_llm"], base_url=self.config["backend_url"], timeout=120, stop=None)
         elif self.config["llm_provider"].lower() == "google":
-            self.deep_thinking_llm = ChatGoogleGenerativeAI(model=self.config["deep_think_llm"])
+            google_api_key = os.getenv("GOOGLE_API_KEY")
-            self.quick_thinking_llm = ChatGoogleGenerativeAI(model=self.config["quick_think_llm"])
+            self.deep_thinking_llm = ChatGoogleGenerativeAI(model=self.config["deep_think_llm"], google_api_key=google_api_key)
+            self.quick_thinking_llm = ChatGoogleGenerativeAI(model=self.config["quick_think_llm"], google_api_key=google_api_key)
         else:
             raise ValueError(f"Unsupported LLM provider: {self.config['llm_provider']}")